Yearly Traffic Safety Analysis

16,480 CRASHES IN
COLUMBUS, OH
2024

All metrics benchmarked against2023

In 2024, Columbus experienced 16,480 total crashes, a slight increase of 1.01% from the 16,316 crashes recorded in 2023. The most significant year-over-year change was a 34.0% decrease in total fatalities, dropping from 100 in 2023 to 66 in 2024. Total injuries also saw a decrease of 1.6% from 7,936 to 7,809.

16,480

▲ 1.0%was 16,316

Total Crash Events

▼ -34.0%was 100

Persons Killed

7,809

▼ -1.6%was 7,936

Persons Injured

6,622

▼ -5.1%was 6,980

Hit-and-Run Crashes

Note: "Persons Killed" (66) counts individual fatalities across all crash events. "Fatal" in the severity table below (61) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Columbus increased by 1.01% year-over-year, from 16,316 in 2023 to 16,480 in 2024. Despite this increase in crash volume, total fatalities decreased by 34.0%, from 100 to 66. Similarly, total injuries declined by 1.6%, from 7,936 to 7,809.

6,622

Hit-and-Run Crashes — 2024

▼ -5.1% vs prior (6,980)

Hit-and-run crashes decreased by 5.1% year-over-year, from 6,980 in 2023 to 6,622 in 2024. The proportion of all crashes classified as hit-and-run also declined, from 42.8% in 2023 to 40.2% in 2024. This indicates a downward trend in both the count and rate of hit-and-run incidents.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 27↓-33.3%

Motorists Killed

Prior: 73↓-34.2%

453

Pedestrians Injured

Prior: 440↑3.0%

7,356

Motorists Injured

Prior: 7,496↓-1.9%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes remained consistent, with Friday being the peak day for crashes in both 2023 (2,691 crashes) and 2024 (2,710 crashes). The peak hour for crashes also remained at 5 PM in both years, increasing slightly from 1,217 crashes in 2023 to 1,315 crashes in 2024.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate decreased from 0.56% in 2023 to 0.37% in 2024, corresponding to a 33.0% reduction in fatal crashes (from 91 to 61). While serious injury crashes (A) decreased by 6.0% (from 383 to 360) and minor injury crashes (B) decreased by 3.2% (from 3,170 to 3,070), possible injury crashes (C) increased by 8.2% (from 1,922 to 2,080).

Severity is per crash event (most severe injury). 61 fatal crash events resulted in 66 persons killed.

Outcome by Severity (Crash Events)

Fatal61fatal crashes0.4%

↓-33.0%prior 91

Serious Injury360serious injury crashes2.2%

↓-6.0%prior 383

Minor Injury3,070minor injury crashes18.6%

↓-3.2%prior 3,170

Possible Injury2,080possible injury crashes12.6%

↑8.2%prior 1,922

No Injury10,909no injury crashes66.2%

↑1.5%prior 10,750

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring in clear weather conditions slightly increased their proportion from 66.4% in 2023 to 66.8% in 2024, while crashes in snowy conditions saw an increase from 1.2% to 2.0%. There was a minor shift in lighting conditions, with daylight crashes increasing from 59.0% to 60.4% and crashes in dark conditions (lighted or not) decreasing from 32.5% to 31.0%. The proportion of crashes on dry road surfaces decreased from 79.4% to 77.9%, while crashes on wet roads increased from 17.6% to 18.1%, and crashes on snowy roads increased from 0.8% to 1.6%.

Weather

Clear11,012 (66.8%)

↑1.6%prior 10,840

Cloudy2,717 (16.5%)

↓-6.5%prior 2,905

Rain2,009 (12.2%)

↑2.7%prior 1,956

Other/Unknown342 (2.1%)

↓-7.6%prior 370

Snow328 (2.0%)

↑65.7%prior 198

Fog; Smog; Smoke37 (0.2%)

↑19.4%prior 31

Sleet; Hail16 (0.1%)

↑166.7%prior 6

Freezing Rain or Freezing Drizzle15 (0.1%)

↑150.0%prior 6

Severe Crosswinds3 (0.0%)

Blowing Sand; Soil; Dirt; Snow1 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight9,956 (60.4%)

↑3.4%prior 9,630

Dark - Lighted Roadway4,279 (26.0%)

↓-3.6%prior 4,441

Dawn/Dusk953 (5.8%)

↑6.5%prior 895

Dark - Roadway Not Lighted822 (5.0%)

↓-4.6%prior 862

Other/Unknown280 (1.7%)

↓-0.7%prior 282

Dark - Unknown Roadway Lighting190 (1.2%)

↓-7.8%prior 206

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry12,840 (77.9%)

↓-0.8%prior 12,948

Wet2,981 (18.1%)

↑4.0%prior 2,865

Other/Unknown310 (1.9%)

↑2.6%prior 302

Snow265 (1.6%)

↑110.3%prior 126

Ice61 (0.4%)

↑15.1%prior 53

Water (Standing; Moving)9 (0.1%)

↑28.6%prior 7

Sand; Mud; Dirt; Oil; Gravel8 (0.0%)

↑14.3%prior 7

Slush6 (0.0%)

↓-25.0%prior 8

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 1.1%, from 32,724 in 2023 to 33,081 in 2024. Passenger cars and SUVs both saw increases in involvement, with passenger cars up by 527 and SUVs up by 467. Honda maintained its position as the top make, increasing its involvement from 3,779 to 4,176, while Chevrolet dropped to second place with a decrease of 119 vehicles.

Top Vehicle Makes (33,081 vehicles)

HONDA4,176 (12.6%)

↑10.5%prior 3,779

CHEVROLET3,588 (10.8%)

↓-3.2%prior 3,707

FORD3,447 (10.4%)

↓-3.6%prior 3,574

TOYOTA3,413 (10.3%)

↑8.9%prior 3,133

NISSAN1,783 (5.4%)

↑5.5%prior 1,690

HYUNDAI1,523 (4.6%)

↑0.1%prior 1,521

KIA1,195 (3.6%)

↓-2.8%prior 1,229

DODGE1,147 (3.5%)

↓-7.1%prior 1,234

JEEP918 (2.8%)

↓-0.5%prior 923

GMC688 (2.1%)

↑4.6%prior 658

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

6,548 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (36,152 persons with recorded sex)

Male20,623 (57.0%)

↑3.1%prior 20,004

Female15,529 (43.0%)

↑0.2%prior 15,494

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Ohio Crash Data (ODOT TIMS), accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

Access method: Csv Open Data API (SoQL queries)
Data format: Structured JSON via REST API
Record types queried: Crash events, person records, and vehicle unit records
Date filter applied: 2024-01-01 through 2024-12-31
Report generated: July 5, 2026

Data Coverage

Reporting period: 2024-01-01 through 2024-12-31 (366 days)
Geographic scope: Columbus, OH
Total crash records analyzed: 16,480
Total persons involved: 40,812
Total vehicles involved: 33,081

Analytical Methodology

Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "Columbus, OH Crash Intelligence Report: 2024." Published July 5, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/columbus/2024-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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16,480 CRASHES INCOLUMBUS, OH2024